We modeled Multilayer Perceptron (MLP) Artificial Neural Network for predicting band diagrams (BD) of bi-dimensional photonic crystals. Datasets for MLP training were created by relating geometric and material properties ...

We modeled Multilayer Perceptron (MLP) Artificial Neural Network for predicting band diagrams (BD) of bi-dimensional photonic crystals. Datasets for MLP training were created by relating geometric and material properties ...

We modeled Multilayer Perceptron and Extreme Learning Machine Artificial Neural Networks (ANNs) for computing band structures (BSTs) and photonic band gaps (PBGs) of 2D and 3D photonic crystals (PhCs). We aim at providing ...

Elaboration of low-losses highly non linear chalcogenide optical fibers for the generation of efficient non linear effects in the infrared remains a challenge. In recent years, much work has been devoted to the study of ...

Elaboration of low-losses highly non linear chalcogenide optical fibers for the generation of efficient non linear effects in the infrared remains a challenge. In recent years, much work has been devoted to the study of ...

We address the bandgap effect and the thermo-optical response of high-index liquid crystal (LC) infiltrated in photonic crystal fibers (PCF) and in hybrid photonic crystal fibers (HPCF). The PCF and HPCF consist of solid-core ...

We address the bandgap effect and the thermo-optical response of high-index liquid crystal (LC) infiltrated in photonic crystal fibers (PCF) and in hybrid photonic crystal fibers (HPCF). The PCF and HPCF consist of solid-core ...

Slow light propagation through photonic crystal (PhC) slab devices has great potential to reduce the size and power consumption of silicon photonic optical circuits. Most commonly, slow light routing through photonic ...